US Semiconductor Stocks Plunge 10% in a Day: The Unraveling of the AI Compute Faith

Historic Single-Day Collapse of the U.S. Semiconductor Sector: A De-Mythologization Ceremony for the AI Computing-Power Faith

On June 7, 2024, the Philadelphia Semiconductor Index (SOX) plunged 10.1%—its steepest single-day drop since the pandemic-induced panic sell-off of March 2020. NVIDIA’s stock tumbled 9.5%, erasing approximately $300 billion in market capitalization—roughly equivalent to the GDP of a mid-sized economy. Micron Technology fell 14.7%, AMD dropped 11.2%, Marvell Technology slid 12.3%, and TSMC’s ADR declined 8.9%. The entire sector shed over $1.3 trillion in market value in one day. This was no technical correction—it was a collective reckoning with the narrative of an “AI computing-power perpetual motion machine,” its deep tremors emanating from fractures across three structural pillars: industrial logic, capital discipline, and geopolitical technological sovereignty.

I. The Trigger: Broadcom’s Earnings Report Tears Open the First Crack in the “High-Growth Illusion”

Markets widely attribute this collapse to Broadcom’s Q2 FY2024 earnings report, released after hours on June 6. Although revenue rose 14% year-on-year to $9.78 billion and net income grew 21%, critical warning signals were glaring: the company significantly lowered its full-year 2024 guidance for AI chip shipments (primarily custom ASICs), citing “slowed procurement timelines for next-generation AI accelerators among certain cloud customers.” Even more consequential was CEO Hock Tan’s candid remark on the earnings call: “We’re observing data center customers shifting from a ‘performance-first’ mindset to a rational purchasing approach constrained by both unit computational cost-efficiency and delivery certainty.” This amounted to a public declaration that AI capital expenditures (CapEx) do not follow an “infinite upward trajectory”—their growth rate has already hit triple ceilings: physical, financial, and organizational.

Broadcom is no outlier. Earlier, Micron had warned that the DRAM inventory cycle would peak in Q3; AMD acknowledged slower-than-expected yield ramp-up for its MI300 series; and TSMC quietly pushed back its 2nm mass-production timeline. These scattered signals converged and resonated under the catalyst of Broadcom’s report, triggering algorithmic trading systems to reprice the entire “AI computing-power value chain”: from upstream equipment (ASML), foundry services (TSMC), chip design (NVIDIA/AMD), memory (Micron), OSAT (ASE), to downstream cloud providers (Microsoft/Google)—causing valuation anchors across the board to collectively loosen.

II. The Underlying Crisis: Three Structural Turning Points Converging Simultaneously

This plunge reflects the synchronous convergence of three cyclical turning points:

First, questions about the sustainability of CapEx. NVIDIA’s data center business is projected to generate $55 billion in revenue in 2024—75% of its total—yet its primary customers (Microsoft, Google, Meta) posted just a 28% year-on-year increase in cloud CapEx in Q1 2024, down sharply from 42% in Q4 2023. As Goldman Sachs notes, today’s AI servers exceed 15 kW per unit in power consumption, and thermal management and electrical infrastructure bottlenecks are now compelling customers to shift toward “computing-power leasing” rather than building private clusters—directly weakening the structural demand for chips.

Second, the inventory cycle entering a passive destocking phase. SEMI data shows the global semiconductor inventory-to-sales ratio rose to 2.1 in Q1 2024—the highest since 2022. Notably, AI GPU inventory days have surged beyond 120—well above the healthy range of 60–90 days. Once the “sales-driven” model falters, procurement reverts to being “demand-driven,” dramatically raising the risk of price wars.

Third, the reallocation of value driven by the geopolitical contest over technological sovereignty. Google’s $30-billion agreement with SpaceX to procure Starlink satellite-based computing power may appear, on the surface, to be an edge-computing experiment—but it signals a deeper strategic pivot: bypassing the traditional cloud intermediaries (AWS/Azure/GCP) to access foundational computing resources directly. This implies that the locus of value in future AI infrastructure is shifting—from “chip performance metrics” (e.g., TOPS/Watt) to “computing-power access sovereignty” (i.e., control over access). Whoever commands scheduling authority over computing resources, data sovereignty, and physical infrastructure control holds the upper hand in pricing negotiations—a paradigm-shifting challenge for chip design firms reliant on IP licensing and fabless business models.

III. Regulatory Mirroring: China’s Capital Markets Precisely Correcting “Thematic Speculation”

Notably, during the same week as the U.S. semiconductor crash, China Securities Regulatory Commission (CSRC) Chairman Wu Qing issued a series of strong regulatory signals: first, cracking down rigorously on chronic abuses by mutual funds—including “betting on hot themes,” “style drift,” and “high-price IPOs”—while emphasizing “counter-cyclical thinking” and “medium-to-long-term returns”; second, strengthening oversight of algorithmic trading to prevent technological misuse from disrupting market order. Though seemingly distant, this reveals the same underlying logic: when a technology bubble inflates beyond fundamental support, regulation inevitably serves as a mandatory, market-purifying calibration mechanism.

The coordinated cleanup of mainland illegal operations by cross-border brokers—including Futu, Tiger Brokers, Longbridge, and华盛 (Huasheng)—was no coincidence. These platforms had previously lured retail investors into volatile AI-related stocks using “zero-commission” offers and leveraged U.S. equity trading—amplifying market irrationality. Regulators’ targeting of distribution channels, in essence, severs the “empty-capital arbitrage” loop, forcing capital back toward intrinsic industrial value—a regulatory philosophy that resonates across markets with the U.S. market’s crash-driven “de-mythologization of faith.”

IV. Restructuring Underway: The Silent Migration of Value Allocation

The collapse is not an endpoint—but the prologue to a new order. Three restructuring pathways are already emerging:

• Rising premium for packaging and advanced interconnect technologies: TSMC’s CoWoS capacity utilization remains above 95%, while orders at traditional packaging houses decline. As compute density increases, “how to interconnect chips” is becoming scarcer—and more valuable—than “how to manufacture them.”
• Accelerated vertical integration upstream by cloud providers: Microsoft Azure has partnered with TSMC to co-build an AI chip production line; Google’s TPU v6 will adopt Samsung’s 2nm GAA process. Cloud giants are transforming from “chip buyers” into “technology definers.”
• Geopolitical security emerging as a new valuation factor: Amid heightened tensions in the Strait of Hormuz (U.S. military and Iranian missile posturing), the “political accessibility” of semiconductor supply chains is now being integrated into institutional investors’ ESG evaluation frameworks. Companies with multi-regional manufacturing capabilities—such as TSMC’s Arizona fab or Samsung’s Texas plant—are receiving risk-premium compensation.

When markets stop paying premiums for “the next trillion-parameter model” and instead begin calculating “carbon footprint per watt of computing power,” “geopolitical risk cost per millisecond of latency,” and “degree of autonomy and controllability per packaging interface,” the semiconductor industry’s valuation framework has quietly transitioned from “techno-optimism” into a new era of “engineering realism.” What this collapse has truly destroyed was never the chips themselves—but humanity’s blind faith in linear technological progress. And what will be rebuilt upon this rubble must rest on three foundations: more disciplined capital allocation, more resilient supply chains, and a clearer-eyed awareness of technological sovereignty.